flinkFlink 1.12.2 源码浅析 : Task 浅析
Posted 九师兄
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1.概述
转载：Flink 1.12.2 源码浅析 : Task 浅析
Task 表示TaskManager上并行 subtask 的一次执行。
Task封装了一个Flink operator（也可能是一个用户function ）并运行它，
提供使用输入数据、生成结果（中间结果分区）和与JobManager通信所需的所有服务。
Flink操作符（实现为{@link AbstractInvokable}的子类）只有数据读取器、编写器和某些事件回调。
该任务将它们连接到网络堆栈和actor消息，并跟踪执行状态和处理异常。、
Task不知道它们与其他任务的关系，也不知道它们是第一次尝试执行任务还是重复执行任务。
所有这些只有JobManager知道。
T只知道自己的可运行代码、任务的配置以及要使用和生成的 intermediate results 的id（如果有的话）。
每个任务由一个专用线程运行。
二 .代码浅析
Task是一个类, 实现了Runnable 接口…
2.1. 属性
/**
* 线程组 包含所有 task thread ..
* The thread group that contains all task threads.
* */
private static final ThreadGroup TASK_THREADS_GROUP = new ThreadGroup("Flink Task Threads");
/**
* 任务状态标识
* For atomic state updates.
* */
private static final AtomicReferenceFieldUpdater<Task, ExecutionState> STATE_UPDATER =
AtomicReferenceFieldUpdater.newUpdater( Task.class, ExecutionState.class, "executionState");
// ------------------------------------------------------------------------
// 属性字段 : Task构造方法初始化中的一部分属性.
// Constant fields that are part of the initial Task construction
// ------------------------------------------------------------------------
/**
* JobID
* The job that the task belongs to. */
private final JobID jobId;
/**
* 当前任务在JobGraph所属的 job vertex id
* The vertex in the JobGraph whose code the task executes. */
private final JobVertexID vertexId;
/**
* 在ExecutionGraph中 子任务所属的 ExecutionAttemptID
* The execution attempt of the parallel subtask.
* */
private final ExecutionAttemptID executionId;
/**
* 在同一个slot中运行锁分配的AllocationID
* ID which identifies the slot in which the task is supposed to run.
* */
private final AllocationID allocationId;
/**
* 任务的相关信息.
* TaskInfo object for this task. */
private final TaskInfo taskInfo;
/**
* 任务名称,包含子任务的索引.
* The name of the task, including subtask indexes.
* */
private final String taskNameWithSubtask;
/**
* job的配置相关信息
* The job-wide configuration object.
* */
private final Configuration jobConfiguration;
/**
* task指定的配置信息.
* The task-specific configuration.
* */
private final Configuration taskConfiguration;
/**
* task任务需所需要的jar文件
* The jar files used by this task.
* */
private final Collection<PermanentBlobKey> requiredJarFiles;
/**
* classpaths相关
* The classpaths used by this task.
* */
private final Collection<URL> requiredClasspaths;
/**
* 该任务的实例化类型
* 1. org.apache.flink.streaming.runtime.tasks.SourceStreamTask
* 2. org.apache.flink.streaming.runtime.tasks.OneInputStreamTask
*
* The name of the class that holds the invokable code.
* */
private final String nameOfInvokableClass;
/**
* 访问 task manager 配置/host name 相关信息
* Access to task manager configuration and host names.
* */
private final TaskManagerRuntimeInfo taskManagerConfig;
/**
* 内存管理相关.
* The memory manager to be used by this task.
* */
private final MemoryManager memoryManager;
/**
* I/O相关
*
* The I/O manager to be used by this task. */
private final IOManager ioManager;
/**
* 广播变量 BroadcastVariableManager
* The BroadcastVariableManager to be used by this task. */
private final BroadcastVariableManager broadcastVariableManager;
/**
* 任务事件的Dispatcher
*/
private final TaskEventDispatcher taskEventDispatcher;
/**
* 外部resources 信息
* Information provider for external resources.
* */
private final ExternalResourceInfoProvider externalResourceInfoProvider;
/**
* task/slot 的状态信息
* The manager for state of operators running in this task/slot.
* */
private final TaskStateManager taskStateManager;
/**
*
* job指定execution配置的序列化相关
* Serialized version of the job specific execution configuration
* (see {@link ExecutionConfig}).
*/
private final SerializedValue<ExecutionConfig> serializedExecutionConfig;
/**
* A record-oriented runtime result writer API for producing results.
*
* ResultPartitionWriter
*/
private final ResultPartitionWriter[] consumableNotifyingPartitionWriters;
/**
* An {@link InputGate} with a specific index.
*/
private final IndexedInputGate[] inputGates;
/**
* task manager的 Connection
* Connection to the task manager.
* */
private final TaskManagerActions taskManagerActions;
/**
*
* Input split provider for the task.
* */
private final InputSplitProvider inputSplitProvider;
/**
* Checkpoint 相关...
* Checkpoint notifier used to communicate with the CheckpointCoordinator.
* */
private final CheckpointResponder checkpointResponder;
/**
* 发送信息给 Job Manager 的Gateway
* The gateway for operators to send messages to the operator coordinators on the Job Manager.
*/
private final TaskOperatorEventGateway operatorCoordinatorEventGateway;
/**
*
* GlobalAggregateManager用于JobMaster的更新和聚合
* GlobalAggregateManager used to update aggregates on the JobMaster.
* */
private final GlobalAggregateManager aggregateManager;
/**
* task请求class loader的时候,加载的library 缓存
* The library cache, from which the task can request its class loader. */
private final LibraryCacheManager.ClassLoaderHandle classLoaderHandle;
/**
* 用户定义的文件的缓存.
* The cache for user-defined files that the invokable requires. */
private final FileCache fileCache;
/**
* task的 kv 状态服务相关.
* The service for kvState registration of this task. */
private final KvStateService kvStateService;
/**
* task启用live reporting of accumulators的注册相关...
* The registry of this task which enables live reporting of accumulators. */
private final AccumulatorRegistry accumulatorRegistry;
/**
* 当前执行task的Thread 线程.
* The thread that executes the task. */
private final Thread executingThread;
/**
* task metrics相关
* Parent group for all metrics of this task. */
private final TaskMetricGroup metrics;
/**
* 分区相关...
* Partition producer state checker to request partition states from.
* */
private final PartitionProducerStateChecker partitionProducerStateChecker;
/**
* Executor ????
* Executor to run future callbacks. */
private final Executor executor;
/**
*
* 当执行一次run方法的Future 索引...
* Future that is completed once {@link #run()} exits.
*
* */
private final CompletableFuture<ExecutionState> terminationFuture = new CompletableFuture<>();
// ------------------------------------------------------------------------
// 属性控制task的执行. 所有的字段是volatile .
// Fields that control the task execution. All these fields are volatile
// (which means that they introduce memory barriers), to establish
// proper happens-before semantics on parallel modification
// ------------------------------------------------------------------------
/**
* 是否取消 : 默认false
* atomic flag that makes sure the invokable is canceled exactly once upon error. */
private final AtomicBoolean invokableHasBeenCanceled;
/**
* task 的 invokable
* 所有的请求必须复制其引用,并检查是否为null
* 作为逻辑处理中的一部分,该字段将会被清理...
* ???????
*
* The invokable of this task, if initialized.
*
* All accesses must copy the reference and check for null,
* as this field is cleared as part of the disposal logic.
*
*/
@Nullable private volatile AbstractInvokable invokable;
/**
* 任务的状态
* The current execution state of the task. */
private volatile ExecutionState executionState = ExecutionState.CREATED;
/** The observed exception, in case the task execution failed. */
private volatile Throwable failureCause;
/**
* 默认值 : 30000 ???
* Initialized from the Flink configuration. May also be set at the ExecutionConfig */
private long taskCancellationInterval;
/**
* 根据Flink 配置进行初始化, 也可在ExecutionConfig中设置.
* Initialized from the Flink configuration.
* May also be set at the ExecutionConfig */
private long taskCancellationTimeout;
/**
* 用户代码类加载器
* This class loader should be set as the context class loader for threads that may dynamically
* load user code.
*/
private UserCodeClassLoader userCodeClassLoader;
2.2. 构造方法
/**
* <b>IMPORTANT:</b> This constructor may not start any work that would need to be undone in the
* case of a failing task deployment.
*/
public Task(
JobInformation jobInformation,
TaskInformation taskInformation,
ExecutionAttemptID executionAttemptID,
AllocationID slotAllocationId,
int subtaskIndex,
int attemptNumber,
List<ResultPartitionDeploymentDescriptor> resultPartitionDeploymentDescriptors,
List<InputGateDeploymentDescriptor> inputGateDeploymentDescriptors,
int targetSlotNumber,
MemoryManager memManager,
IOManager ioManager,
ShuffleEnvironment<?, ?> shuffleEnvironment,
KvStateService kvStateService,
BroadcastVariableManager bcVarManager,
TaskEventDispatcher taskEventDispatcher,
ExternalResourceInfoProvider externalResourceInfoProvider,
TaskStateManager taskStateManager,
TaskManagerActions taskManagerActions,
InputSplitProvider inputSplitProvider,
CheckpointResponder checkpointResponder,
TaskOperatorEventGateway operatorCoordinatorEventGateway,
GlobalAggregateManager aggregateManager,
LibraryCacheManager.ClassLoaderHandle classLoaderHandle,
FileCache fileCache,
TaskManagerRuntimeInfo taskManagerConfig,
@Nonnull TaskMetricGroup metricGroup,
ResultPartitionConsumableNotifier resultPartitionConsumableNotifier,
PartitionProducerStateChecker partitionProducerStateChecker,
Executor executor) {
Preconditions.checkNotNull(jobInformation);
Preconditions.checkNotNull(taskInformation);
Preconditions.checkArgument(0 <= subtaskIndex, "The subtask index must be positive.");
Preconditions.checkArgument(0 <= attemptNumber, "The attempt number must be positive.");
Preconditions.checkArgument(
0 <= targetSlotNumber, "The target slot number must be positive.");
this.taskInfo =
new TaskInfo(
taskInformation.getTaskName(),
taskInformation.getMaxNumberOfSubtasks(),
subtaskIndex,
taskInformation.getNumberOfSubtasks(),
attemptNumber,
String.valueOf(slotAllocationId));
this.jobId = jobInformation.getJobId();
this.vertexId = taskInformation.getJobVertexId();
this.executionId = Preconditions.checkNotNull(executionAttemptID);
this.allocationId = Preconditions.checkNotNull(slotAllocationId);
this.taskNameWithSubtask = taskInfo.getTaskNameWithSubtasks();
this.jobConfiguration = jobInformation.getJobConfiguration();
this.taskConfiguration = taskInformation.getTaskConfiguration();
this.requiredJarFiles = jobInformation.getRequiredJarFileBlobKeys();
this.requiredClasspaths = jobInformation.getRequiredClasspathURLs();
this.nameOfInvokableClass = taskInformation.getInvokableClassName();
this.serializedExecutionConfig = jobInformation.getSerializedExecutionConfig();
Configuration tmConfig = taskManagerConfig.getConfiguration();
this.taskCancellationInterval =
tmConfig.getLong(TaskManagerOptions.TASK_CANCELLATION_INTERVAL);
this.taskCancellationTimeout =
tmConfig.getLong(TaskManagerOptions.TASK_CANCELLATION_TIMEOUT);
this.memoryManager = Preconditions.checkNotNull(memManager);
this.ioManager = Preconditions.checkNotNull(ioManager);
this.broadcastVariableManager = Preconditions.checkNotNull(bcVarManager);
this.taskEventDispatcher = Preconditions.checkNotNull(taskEventDispatcher);
this.taskStateManager = Preconditions.checkNotNull(taskStateManager);
this.accumulatorRegistry = new AccumulatorRegistry(jobId, executionId);
this.inputSplitProvider = Preconditions.checkNotNull(inputSplitProvider);
this.checkpointResponder = Preconditions.checkNotNull(checkpointResponder);
this.operatorCoordinatorEventGateway =
Preconditions.checkNotNull(operatorCoordinatorEventGateway);
this.aggregateManager = Preconditions.checkNotNull(aggregateManager);
this.taskManagerActions = checkNotNull(taskManagerActions);
this.externalResourceInfoProvider = checkNotNull(externalResourceInfoProvider);
this.classLoaderHandle = Preconditions.checkNotNull(classLoaderHandle);
this.fileCache = Preconditions.checkNotNull(fileCache);
this.kvStateService = Preconditions.checkNotNull(kvStateService);
this.taskManagerConfig = Preconditions.checkNotNull(taskManagerConfig);
this.metrics = metricGroup;
this.partitionProducerStateChecker =
Preconditions.checkNotNull(partitionProducerStateChecker);
this.executor = Preconditions.checkNotNull(executor);
// create the reader and writer structures
final String taskNameWithSubtaskAndId = taskNameWithSubtask + " (" + executionId + ')';
final ShuffleIOOwnerContext taskShuffleContext =
shuffleEnvironment.createShuffleIOOwnerContext(
taskNameWithSubtaskAndId, executionId, metrics.getIOMetricGroup());
// produced intermediate result partitions
final ResultPartitionWriter[] resultPartitionWriters =
shuffleEnvironment
.createResultPartitionWriters(
taskShuffleContext, resultPartitionDeploymentDescriptors)
.toArray(new ResultPartitionWriter[] {});
this.consumableNotifyingPartitionWriters =
ConsumableNotifyingResultPartitionWriterDecorator.decorate(
resultPartitionDeploymentDescriptors,
resultPartitionWriters,
this,
jobId,
resultPartitionConsumableNotifier);
// consumed intermediate result partitions
final IndexedInputGate[] gates =
shuffleEnvironment
.createInputGates(taskShuffleContext, this, inputGateDeploymentDescriptors)
.toArray(new IndexedInputGate[0]);
this.inputGates = new IndexedInputGate[gates.length];
int counter = 0;
for (IndexedInputGate gate : gates) {
inputGates[counter++] =
new InputGateWithMetrics(
gate, metrics.getIOMetricGroup().getNumBytesInCounter());
}
if (shuffleEnvironment instanceof NettyShuffleEnvironment) {
//noinspection deprecation
((NettyShuffleEnvironment) shuffleEnvironment)
.registerLegacyNetworkMetrics(
metrics.getIOMetricGroup(), resultPartitionWriters, gates);
}
invokableHasBeenCanceled = new AtomicBoolean(false);
// finally, create the executing thread, but do not start it
executingThread = new Thread(TASK_THREADS_GROUP, this, taskNameWithSubtask);
}
2.3. startTaskThread
启动task 线程.
/** Starts the task's thread. */
public void startTaskThread() {
executingThread.start();
}
2.4. doRun
因为Task实现了Runnable接口. 所以启动必须是由Thread类的start启动. 然后调用run()方法.
在执行run方法的时候, 会引导任务并执行其代码的核心工作方法doRun。
/**
* 引导任务并执行其代码的核心工作方法。
* The core work method that bootstraps the task and executes its code.
* */
@Override
public void run() {
try {
doRun();
} finally {
terminationFuture.complete(executionState);
}
}
doRun
private void doRun() {
// ----------------------------
// Initial State transition
// ----------------------------
while (true) {
// 获取当前状态
ExecutionState current = this.executionState;
if (current == ExecutionState.CREATED) {
// 创建&执行
if (transitionState(ExecutionState.CREATED, ExecutionState.DEPLOYING)) {
// success, we can start our work
// 跳出,开始执行任务...
break;
}
} else if (current == ExecutionState.FAILED) {
// 失败
// we were immediately failed. tell the TaskManager that we reached our final state
notifyFinalState();
if (metrics != null) {
metrics.close();
}
return;
} else if (current == ExecutionState.CANCELING) {
// 取消
if (transitionState(ExecutionState.CANCELING, ExecutionState.CANCELED)) {
// we were immediately canceled. tell the TaskManager that we reached our final
// state
notifyFinalState();
if (metrics != null) {
metrics.close();
}
return;
}
} else {
if (metrics != null) {
metrics.close();
}
throw new IllegalStateException(
"Invalid state for beginning of operation of task " + this + '.');
}
}
// 所有从这里获取和注册的资源最终都需要撤消
// all resource acquisitions and registrations from here on
// need to be undone in the end
Map<String, Future<Path>> distributedCacheEntries = new HashMap<>();
AbstractInvokable invokable = null;
try {
// ----------------------------
// 任务引导-我们定期检查是否作为快捷方式取消
// Task Bootstrap - We periodically
// check for canceling as a shortcut
// ----------------------------
// activate safety net for task thread
// Creating FileSystem stream leak safety net for task
//
// Window(TumblingProcessingTimeWindows(5000), ProcessingTimeTrigger, ReduceFunction$1, PassThroughWindowFunction)
// ->
// Sink: Print to Std. Out (1/1)#0 (141dd597dc560a831b2b4bc195943f0b) [DEPLOYING]
//
LOG.debug("Creating FileSystem stream leak safety net for task {}", this);
FileSystemSafetyNet.initializeSafetyNetForThread();
// 首先，获取一个用户代码类加载器这可能涉及下载作业的JAR文件和/或类
// first of all, get a user-code classloader
// this may involve downloading the job's JAR files and/or classes
// 加载Task 所需的JAR
// Loading JAR files for task
// Window(TumblingProcessingTimeWindows(5000), ProcessingTimeTrigger, ReduceFunction$1, PassThroughWindowFunction) -> Sink: Print to Std. Out (1/1)#0 (141dd597dc560a831b2b4bc195943f0b) [DEPLOYING].
LOG.info("Loading JAR files for task {}.", this);
// 获取用户类加载器 : UserCodeClassLoader
// Getting user code class loader for task 141dd597dc560a831b2b4bc195943f0b at library cache manager took 10 milliseconds
userCodeClassLoader = createUserCodeClassloader();
final ExecutionConfig executionConfig =
serializedExecutionConfig.deserializeValue(userCodeClassLoader.asClassLoader());
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